Mastercard’s Big Data For Good Initiative: Data Philanthropy On The Front Lines


Interview by Randy Bean of Shamina Singh: Much has been written about big data initiatives and the efforts of market leaders to derive critical business insights faster. Less has been written about initiatives by some of these same firms to apply big data and analytics to a different set of issues, which are not solely focused on revenue growth or bottom line profitability. While the focus of most writing has been on the use of data for competitive advantage, a small set of companies has been undertaking, with much less fanfare, a range of initiatives designed to ensure that data can be applied not just for corporate good, but also for social good.

One such firm is Mastercard, which describes itself as a technology company in the payments industry, which connects buyers and sellers in 210 countries and territories across the globe. In 2013 Mastercard launched the Mastercard Center for Inclusive Growth, which operates as an independent subsidiary of Mastercard and is focused on the application of data to a range of issues for social benefit….

In testimony before the Senate Committee on Foreign Affairs on May 4, 2017, Mastercard Vice Chairman Walt Macnee, who serves as the Chairman of the Center for Inclusive Growth, addressed issues of private sector engagement. Macnee noted, “The private sector and public sector can each serve as a force for good independently; however when the public and private sectors work together, they unlock the potential to achieve even more.” Macnee further commented, “We will continue to leverage our technology, data, and know-how in an effort to solve many of the world’s most pressing problems. It is the right thing to do, and it is also good for business.”…

Central to the mission of the Mastercard Center is the notion of “data philanthropy”. This term encompasses notions of data collaboration and data sharing and is at the heart of the initiatives that the Center is undertaking. The three cornerstones on the Center’s mandate are:

  • Sharing Data Insights– This is achieved through the concept of “data grants”, which entails granting access to proprietary insights in support of social initiatives in a way that fully protects consumer privacy.
  • Data Knowledge – The Mastercard Center undertakes collaborations with not-for-profit and governmental organizations on a range of initiatives. One such effort was in collaboration with the Obama White House’s Data-Driven Justice Initiative, by which data was used to help advance criminal justice reform. This initiative was then able, through the use of insights provided by Mastercard, to demonstrate the impact crime has on merchant locations and local job opportunities in Baltimore.
  • Leveraging Expertise – Similarly, the Mastercard Center has collaborated with private organizations such as DataKind, which undertakes data science initiatives for social good.Just this past month, the Mastercard Center released initial findings from its Data Exploration: Neighborhood Crime and Local Business initiative. This effort was focused on ways in which Mastercard’s proprietary insights could be combined with public data on commercial robberies to help understand the potential relationships between criminal activity and business closings. A preliminary analysis showed a spike in commercial robberies followed by an increase in bar and nightclub closings. These analyses help community and business leaders understand factors that can impact business success.Late last year, Ms. Singh issued A Call to Action on Data Philanthropy, in which she challenges her industry peers to look at ways in which they can make a difference — “I urge colleagues at other companies to review their data assets to see how they may be leveraged for the benefit of society.” She concludes, “the sheer abundance of data available today offers an unprecedented opportunity to transform the world for good.”….(More)

Data Responsibility: Social Responsibility for a Data Age


TED-X Talk by Stefaan Verhulst: “In April 2015, the Gorkha earthquake hit Nepal—the worst in more than 80 years. Hundreds of thousands of people were rendered homeless and entire villages were flattened. The earthquake also triggered massive avalanches on Mount Everest, and ultimately killed nearly 9,000 people across the country.

Yet for all the destruction, the toll could have been far greater. Without mitigating or in any way denying the horrible disaster that hit Nepal that day, the responsible use of data helped avoid a worse calamity and may offer lessons for other disasters around the world.

Following the earthquake, government and civil society organizations rushed in to address the humanitarian crisis. Notably, so did the private sector. Nepal’s largest mobile operator, Ncell, for example, decided to share its mobile data—in an aggregated, de-identified way—with the the nonprofit Swedish organization Flowminder. Flowminder then used this data to map population movements around the country; these real-time maps allowed the government and humanitarian organizations to better target aid and relief to affected communities, thus maximizing the impact of their efforts.

The initiative has been widely lauded as a model for cross-sector collaboration. But what is perhaps most striking about the initiative is the way it used data—in particular, how it repurposed data originally collected for private purposes for public ends. This use of corporate data for wider social impact reflects the emerging concept of “data responsibility.” …

 

The Three Pillars of Data Responsibility

1. Share. This is perhaps the most evident: Data holders have a duty to share private data when a clear case exists that it serves the public good. There now exists manifold evidence that data—with appropriate oversight—can help improve lives, as we saw in Nepal.

2. Protect. The consequences of failing to protect data are well documented. The most obvious problems occur when data is not properly anonymized or when de-anonymized data leaks into the public domain. But there are also more subtle cases, when ostensibly anonymized data is itself susceptible to de-anonymization, and information released for the public good ends up causing or potentially causing harm.

3. Act. For the data to really serve the public good, officials and others must create policies and interventions based on the insights they gain from it. Without action, the potential remains just that—mere potential, never translated into concrete results….(Watch TEDx Video).

See also International Data Responsibility Group and Data Collaboratives Project.

Deadly Data Gaps: How Lack of Information Harms Refugee Policy Making


Interview with Galen Englund by Charlotte Alfred: “The U.N. Refugee Agency recently released its annual estimate of the world’s displaced population: 65.6 million. This figure is primarily based on data provided by governments, each using their own definitions and data collection methods.

This leaves ample space for inconsistencies and data gaps. South Africa, for example, reported 463,900 asylum seekers in 20141.1 million in 2015 and then just 218,300 last year. But the number of people had not fluctuated that wildly. What did change was how asylum seekers are counted.

National estimates can also obscure entire groups of people, like internally displaced groups that governments don’t want to acknowledge, notes Galen Englund, who analyzes humanitarian data at the ONE Campaign advocacy organization.

Over the past year, Englund has been digging into the data on refugees and displaced populations for the ONE Campaign. It was an uphill battle. He collected figures from 67 reports that used 356 differently worded metrics in order to identify the needs of displaced populations. “Frequently information is not there, or it’s siloed within organizations, or there’s too much bureaucratic red tape around it, or it just hasn’t been collected yet,” he said.

His research resulted in a displacement tracking platform called Movement, which compiles various U.N. data, and a briefing paper outlining displacement data gaps that concludes: “The information architecture of humanitarian aid is not fit for purpose.” We spoke to Englund about his findings….

Galen Englund: There’s several layers of massive data gaps that all coincide with each other. Probably the most troubling for me is not being able to understand at a granular level where refugees and displaced people are inside of countries, and the transition between when someone leaves their home and becomes displaced, and when they actually cross international borders and become refugees or asylum seekers. That’s an incredibly difficult transition to track, and one that there’s inadequate data on right now….(More)”.

Crowd Research: Open and Scalable University Laboratories


Paper by Rajan Vaish et al: “Research experiences today are limited to a privileged few at select universities. Providing open access to research experiences would enable global upward mobility and increased diversity in the scientific workforce. How can we coordinate a crowd of diverse volunteers on open-ended research? How could a PI have enough visibility into each person’s contributions to recommend them for further study? We present Crowd Research, a crowdsourcing technique that coordinates open-ended research through an iterative cycle of open contribution, synchronous collaboration, and peer assessment. To aid upward mobility and recognize contributions in publications, we introduce a decentralized credit system: participants allocate credits to each other, which a graph centrality algorithm translates into a collectively-created author order. Over 1,500 people from 62 countries have participated, 74% from institutions with low access to research. Over two years and three projects, this crowd has produced articles at top-tier Computer Science venues, and participants have gone on to leading graduate programs….(More)”.

How open data can help the Global South, from disaster relief to voter turnout


Stefaan Verhulst and Andrew Young in The Conversation Global: “The modern era is marked by growing faith in the power of data. “Big data”, “open data”, and “evidence-based decision-making” have become buzzwords, touted as solutions to the world’s most complex and persistent problems, from corruption and famine to the refugee crisis.

While perhaps most pronounced in higher income countries, this trend is now emerging globally. In Africa, Latin America, Asia and beyond, hopes are high that access to data can help developing economies by increasing transparency, fostering sustainable development, building climate resiliency and the like.

This is an exciting prospect, but can opening up data actually make a difference in people’s lives?

Getting data-driven about data

The GovLab at New York University spent the last year trying to answer that question….

Our conclusion: the enthusiasm is justified – as long as it’s tempered with a good measure of realism, too. Here are our six major takeaways:

1. We need a framework – Overall, there is still little evidence to substantiate the enthusiastic claims that open data can foment sustainable development and transform governance. That’s not surprising given the early stage of most open data initiatives.

It may be early for impact evaluation, but it’s not too soon to develop a model that will eventually allow us to assess the impact of opening up data over time.

To that end, the GovLab has created an evidence-based framework that aims to better capture the role of open data in developing countries. The Open Data Logic Framework below focuses on various points in the open data value cycle, from data supply to demand, use and impact.

Logic model of open data. The GovLab

2. Open data has real promise – Based on this framework and the underlying evidence that fed into it, we can guardedly conclude that open data does in fact spur development – but only under certain conditions and within the right supporting ecosystem.

One well-known success took place after Nepal’s 2015 earthquake when open data helped NGOs map important landmarks such as health facilities and road networks, among other uses.

And in Colombia, the International Centre for Tropical Agriculture launched Aclímate Colombia, a tool that gives smallholder farmers data-driven insight into planting strategies that makes them more resilient to climate change….

3. Open data can improve people’s lives Examining projects in a number of sectors critical to development, including health, humanitarian aid, agriculture, poverty alleviation, energy and education, we found four main ways that data can have an impact….

4. Data can be an asset in development While these impacts are apparent in both developed and developing countries, we believe that open data can have a particularly powerful role in developing economies.

Where data is scarce, as it often is in poorer countries, open data can lead to an inherently more equitable and democratic distribution of information and knowledge. This, in turn, may activate a wider range of expertise to address complex problems; it’s what we in the field call “open innovation”.

This quality can allow resource-starved developing economies to access and leverage the best minds around.

And because trust in government is quite low in many developing economies, the transparency bred of releasing data can have after-effects that go well beyond the immediate impact of the data itself…

5. The ingredients matter To better understand why some open data projects fail while others succeed, we created a “periodic table” of open data (below), which includes 27 enabling factors divided into five broad categories….

6. We can plan for impact Our report ends by identifying how development organisations can catalyse the release and use of open data to make a difference on the ground.

Recommendations include:

· Define the problem, understand the user, and be aware of local conditions;

· Focus on readiness, responsiveness and change management;

· Nurture an open data ecosystem through collaboration and partnerships;

· Have a risk mitigation strategy;

· Secure resources and focus on sustainability; and

· Build a strong evidence base and support more research.

Next steps

In short, while it may still be too early to fully capture open data’s as-of-yet muted impact on developing economies, there are certainly reasons for optimism.

Much like blockchaindrones and other much-hyped technical advances, it’s time to start substantiating the excitement over open data with real, hard evidence.

The next step is to get systematic, using the kind of analytical framework we present here to gain comparative and actionable insight into if, when and how open data works. Only by getting data-driven about open data can we help it live up to its potential….(More)

Intelligent sharing: unleashing the potential of health and care data in the UK to transform outcomes


Report by Future Care Capital: “….Data is often referred to as the ‘new oil’ – the 21st century raw material which, when hitched to algorithmic refinement, may be mined for insight and value – and ‘data flows’ are said to have exerted a greater impact upon global growth than traditional goods flows in recent years (Manyika et al, 2016). Small wonder, then, that governments around the world are endeavouring to strike a balance between individual privacy rights and protections on the one hand, and organisational permissions to facilitate the creation of social, economic and environmental value from broad-ranging data on the other: ‘data rights’ are now of critical importance courtesy of technological advancements. The tension between the two is particularly evident where health and care data in the UK is concerned. Individuals are broadly content with anonymised data from their medical records being used for public benefit but are, understandably, anxious about the implications of the most intimate aspects of their lives being hacked or, else, shared without their knowledge or consent….

The potential for health and care data to be transformative remains, and there is growing concern that opportunities to improve the use of health and care data in peoples’ interests are being missed….

we recommend additional support for digitisation efforts in social care settings. We call upon the Government to streamline processes associated with Information Governance (IG) modelling to help data sharing initiatives that traverse organisational boundaries. We also advocate for investment and additional legal safeguards to make more anonymised data sets available for research and innovation. Crucially, we recommend expediting the scope for individuals to contribute health and care data to sharing initiatives led by the public sector through promotion, education and pilot activities – so that data is deployed to transform public health and support the ‘pivot to prevention’.

In Chapter Two, we explore the rationale and scope for the UK to build upon emergent practice from around the world and become a global leader in ‘data philanthropy’ – to push at the boundaries of existing plans and programmes, and support the development of and access to unrivalled health and care data sets. We look at member-controlled ‘data cooperatives’ and what we’ve termed ‘data communities’ operated by trusted intermediaries. We also explore ‘data collaboratives’ which involve the private sector engaging in data philanthropy for public benefit. Here, we make recommendations about promoting a culture of data philanthropy through the demonstration of tangible benefits to participants and the wider public, and we call upon Government to assess the appetite and feasibility of establishing the world’s first National Health and Care Data Donor Bank….(More)”

 

NIH-funded team uses smartphone data in global study of physical activity


National Institutes of Health: “Using a larger dataset than for any previous human movement study, National Institutes of Health-funded researchers at Stanford University in Palo Alto, California, have tracked physical activity by population for more than 100 countries. Their research follows on a recent estimate that more than 5 million people die each year from causes associated with inactivity.

The large-scale study of daily step data from anonymous smartphone users dials in on how countries, genders, and community types fare in terms of physical activity and what results may mean for intervention efforts around physical activity and obesity. The study was published July 10, 2017, in the advance online edition of Nature.

“Big data is not just about big numbers, but also the patterns that can explain important health trends,” said Grace Peng, Ph.D., director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) program in Computational Modeling, Simulation and Analysis.

“Data science and modeling can be immensely powerful tools. They can aid in harnessing and analyzing all the personalized data that we get from our phones and wearable devices.”

Almost three quarters of adults in developed countries and half of adults in developing economies carry a smartphone. The devices are equipped with tiny accelerometers, computer chip that maintains the orientation of the screen, and can also automatically record stepping motions. The users whose data contributed to this study subscribed to the Azumio Argus app, a free application for tracking physical activity and other health behaviors….

In addition to the step records, the researchers accessed age, gender, and height and weight status of users who registered the smartphone app. They used the same calculation that economists use for income inequality — called the Gini index — to calculate activity inequality by country.

“These results reveal how much of a population is activity-rich, and how much of a population is activity-poor,” Delp said. “In regions with high activity inequality there are many people who are activity poor, and activity inequality is a strong predictor of health outcomes.”…

The researchers investigated the idea that making improvements in a city’s walkability — creating an environment that is safe and enjoyable to walk — could reduce activity inequality and the activity gender gap.

“If you must cross major highways to get from point A to point B in a city, the walkability is low; people rely on cars,” Delp said. “In cities like New York and San Francisco, where you can get across town on foot safely, the city has high walkability.”

Data from 69 U.S. cities showed that higher walkability scores are associated with lower activity inequality. Higher walkability is associated with significantly more daily steps across all age, gender, and body-mass-index categories.  However, the researchers found that women recorded comparatively less activity than men in places that are less walkable.

The study exemplifies how smartphones can deliver new insights about key health behaviors, including what the authors categorize as the global pandemic of physical inactivity….(More)”.

Big Data, Data Science, and Civil Rights


Paper by Solon Barocas, Elizabeth Bradley, Vasant Honavar, and Foster Provost:  “Advances in data analytics bring with them civil rights implications. Data-driven and algorithmic decision making increasingly determine how businesses target advertisements to consumers, how police departments monitor individuals or groups, how banks decide who gets a loan and who does not, how employers hire, how colleges and universities make admissions and financial aid decisions, and much more. As data-driven decisions increasingly affect every corner of our lives, there is an urgent need to ensure they do not become instruments of discrimination, barriers to equality, threats to social justice, and sources of unfairness. In this paper, we argue for a concrete research agenda aimed at addressing these concerns, comprising five areas of emphasis: (i) Determining if models and modeling procedures exhibit objectionable bias; (ii) Building awareness of fairness into machine learning methods; (iii) Improving the transparency and control of data- and model-driven decision making; (iv) Looking beyond the algorithm(s) for sources of bias and unfairness—in the myriad human decisions made during the problem formulation and modeling process; and (v) Supporting the cross-disciplinary scholarship necessary to do all of that well…(More)”.

6 Jurisdictions Tackling Homelessness with Technology


 in GovernmentTechnology: “Public servants who work to reduce homelessness often have similar lists of challenges.

The most common of these are data sharing between groups involved with the homeless, the ability to track interactions between individuals and outreach providers, and a system that makes it easier to enter information about the population. Recently, we spoke with more than a half-dozen government officials who are involved with the homeless, and while obstacles and conditions varied among cities, all agreed that their work would be much easier with better tech-based solutions for the problems cited above.

These officials, however, were uniformly optimistic that such solutions were becoming more readily available — solutions with potential to solve the logistical hurdles that most often hamstring government, community and nonprofit efforts to help the homeless find jobs, residences and medical care. Some agencies, in fact, have already had success implementing tech as components in larger campaigns, while others are testing new platforms that may bolster organization and efficiency.

Below are a few brief vignettes that detail some — but far from all — ongoing governmental efforts to use tech to aid and reduce the homeless population.

1. BERGEN COUNTY, N.J.

One of the best examples of government using tech to address homelessness can be found in Bergen County, N.J., where officials recently certified their jurisdiction as first in the nation to end chronic homelessness. READ MORE

2. AURORA, COLO.

Aurora, Colo., in the Denver metropolitan, area uses the Homeless Management Information System required by the U.S. Department of Housing and Urban Development, but those involved with addressing homelessness there have also developed tech-based efforts that are specifically tailored to the area’s needs. READ MORE

4. NEW YORK CITY

New York City is rolling out an app called StreetSmart, which enables homelessness outreach workers in all five boroughs to communicate and log data seamlessly in real time while in the field. With StreetSmart, these workers will be able to enter that information into a single citywide database as they collect it. READ MORE(Full article)

Policymakers around the world are embracing behavioural science


The Economist: “In 2013 thousands of school pupils in England received a letter from a student named Ben at the University of Bristol. The recipients had just gained good marks in their GCSEs, exams normally taken at age 16. But they attended schools where few pupils progressed to university at age 18, and those that did were likely to go to their nearest one. That suggested the schools were poor at nurturing aspiration. In his letter Ben explained that employers cared about the reputation of the university a job applicant has attended. He pointed out that top universities can be a cheaper option for poorer pupils, because they give more financial aid. He added that he had not known these facts at the recipient’s age.

The letters had the effect that was hoped for. A study published in March found that after leaving school, the students who received both Ben’s letter and another, similar one some months later were more likely to be at a prestigious university than those who received just one of the letters, and more likely again than those who received none. For each extra student in a better university, the initiative cost just £45 ($58), much less than universities’ own attempts to broaden their intake. And the approach was less heavy-handed than imposing quotas for poorer pupils, an option previous governments had considered. The education department is considering rolling out the scheme….

Some critics feared that nudges would do little good, and that their effects would fade over time. Others warned that governments were straying perilously close to mass manipulation. More recently, some of the findings on which the behavioural sciences rest have been questioned, as researchers in many fields have sought to replicate famous results, and failed.

By and large those doubts have been allayed. Even if specific results turn out to be mistaken, an experimental, iterative, data-driven approach to policymaking is gaining ground in many places, not just in dedicated units, but throughout government.

Nudging is hardly new. “In Genesis, Satan nudged, and Eve did too,” writes Cass Sunstein of Harvard University. From the middle of the 20th century psychologists such as Stanley Milgram and Philip Zimbardo showed how sensitive humans are to social pressure. Daniel Kahneman and Amos Tversky described the mental shortcuts and biases that influence decision-making. Dale Carnegie and Robert Cialdini wrote popular books on persuasion. Firms, especially in technology, retail and advertising, used behavioural science to shape brand perception and customer behaviour—and, ultimately, to sell more stuff.

But governments’ use of psychological insights to achieve policy goals was occasional and unsystematic. According to David Halpern, the boss of BIT, as far as policymakers were concerned, psychology was “the sickly sibling to economics”. That began to change after Mr Sunstein and Richard Thaler, an economist, published “Nudge”, in 2008. The book attacked the assumption of rational decision-making inherent in most economic models and showed how “choice architecture”, or context, could be changed to “nudge” people to make better choices…..

Now many governments are turning to nudges to save money and do better. In 2014 the White House opened the Social and Behavioural Sciences Team. A report that year by Mark Whitehead of Aberystwyth University counted 51 countries in which “centrally directed policy initiatives” were influenced by behavioural sciences. Non-profit organisations such as Ideas42, set up in 2008 at Harvard University, help run dozens of nudge-style trials and programmes around the world. In 2015 the World Bank set up a group that is now applying behavioural sciences in 52 poor countries. The UN is turning to nudging to help hit the “sustainable development goals”, a list of targets it has set for 2030….

Among the most effective nudges are “social” ones: those that communicate norms or draw on people’s networks. A scheme tested in Guatemala with help from the World Bank and BIT tweaked the wording of letters sent to people and firms who had failed to submit tax returns the previous year. The letters that framed non-payment as an active choice, or noted that paying up is more common than evasion, cut the number of non-payers in the following year and increased the average sum paid. And a trial involving diabetes shows that it matters to nudge at the right moment. In 2014 Hamad Medical Corporation, a health-care provider in Qatar, raised take-up rates for diabetes screening by offering it during Ramadan. That meant most Qataris were fasting, so the need to do so before the test imposed no extra burden….(More)”.